Falls are one of the greatest health risk factors for elderly people. About one third of older people above the age of 65 fall at least once a year.
Many of these falls could be avoided by early identification of fall risk and the application of effective and targeted fall prevention programs. Fall prevention trials based on strength and balance training (SBT) have shown that the risk of falling for elderly people can be reduced.
An important parameter for the assessment of fall risk is the amount of daily activity. For frail elderly people, who are the largest part of the population with a high fall risk, the amount of time that they spend ‘on legs’ (i.e. walking, standing, etc.) over the course of a day provides a useful insight into their fall risk. The parameter “time-on-leg” corresponds to the amount of time that the person is performing particular weight-bearing activities or is in weight-bearing postures like regular/irregular walking, standing, etc. On the other hand, the parameter “time-off-leg” corresponds to the amount of time that the person spends doing non weight-bearing activities or being in non weight-bearing postures like lying, sitting, etc. Continuous or regular monitoring and analysis of “time-on-leg” for a particular person in daily life situations is complementary to standard physical tests for accurate and reliable fall risk assessment.
However, reliable assessment of daily activity or time-on-leg is difficult. The most commonly used approach is for the person themselves to log their activities. However, self-reporting comes with many drawbacks and generally produces unreliable and insufficient information for accurate assessment.
Although, recent development of on-body sensing technology provides objective measures of daily activity, many currently available products are only able to detect and monitor dynamic activities like running and regular walking, which is not particularly relevant when analyzing the daily life of the frail population. Some products do exist that provide analysis of postures, but they require the user to wear the sensors on inconvenient locations such as the thighs. To obtain good compliance in using the assessment tool, the sensor platform should ideally be located on the upper trunk in the form of a pendant-worn or similar device. However, it is difficult to detect postures such as sitting and standing from movement signals obtained using a device in this position.
Therefore, there is a need for a method and apparatus that can identify when a user has transitioned from a sitting posture to a standing posture and vice versa from measurements of the movement of the user. Identifying these posture changes allows an estimation of the time-on-leg for the user. The time-on-leg can be the sum of all time periods when the user is determined not to be sitting or lying down, e.g. following a transition from a sitting posture to a standing posture until the next transition from a standing posture to a sitting posture.